PMean: The Dark Side of Data Science

Steve Simon

2018-08-13

I’m planning to give a talk on “The Dark Side of Data Science” and I’m hoping to get some interesting references and articles from my colleagues. Here is a first draft of my abstract

Progress in statistical modeling has grown faster than our ability to assess the individual and societal impact of these models. We can now attach numbers or labels to people that are surprisingly effective at predicting future behavior

References:

Keith A. Baggerly

I. Glenn Cohen

Gina Kolata. How Bright Promise in Cancer Testing Fell Apart. The New York Times (2011

Cliff Kuang. Can AI Be Taught to Explain Itself. The New York Times (2017

[[[Will Knight. Microsoft is creating an oracle for catching biased AI algorithms. MIT Technology Review (2018

Cathy O’Neil. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown Publishers (2016). ISBN: 978-0553418811. Also check out Cathy O’Neil’s blog: Mathbabe: Exploring and Venting About Quantitative Issues.